Spring's around the corner here in Canada. I embraced the slightly warmer weather (not much snow this winter, so no snow melting), and I got out for my first bike ride of the season near my home. It was one of those moments where you can't help but appreciate the simple pleasures — the kind of day that fills you with a sense of possibility.
This newsletter will focus on exploring the two distinct research categories that most data-gathering exercises can be classified into: qualitative and quantitative UX research.
Most UX researchers start with qualitative research.
I was no exception – except that I studied neuroscience, so I might’ve gotten a bit more quantitative training under my belt. But only in recent years did I open up my horizon and focus on more in-depth quantitative research in my day job.
Let's delve into the differences between quantitative and qualitative research to clear up any confusion.
When we want to measure sets of variables or quantities and their relationship to each other, we use quantitative research methods. Basically, this type of research is all about numbers and objective data.
For example, a person researching the effects of global warming might take temperature measurements over a given amount of time to determine the rate at which the climate changes.
However, when we think about design research, this method is too scientific and can hardly be done successfully in our field. Instead, we usually look into social sciences for a method that better suits our projects’ needs.
Think about the study of consumer behaviour in e-commerce: we might track website traffic, conversion rates, and purchase patterns over a specific period to analyze shopping habits and preferences. This quantitative approach collects and analyzes numerical data to understand how different factors influence online purchasing decisions.
What’s the most used method you can encounter in quant research?
It’s mainly questionnaires or surveys because the responses can be scored and measured using simple statistical calculations. For instance, by surveying user reactions to a new UI design, we can quantitatively assess its appeal and impact on overall user satisfaction. In this context, understanding and leveraging quantitative research methods enable us to systematically explore and validate design decisions, ensuring they resonate well with our target audience.
In contrast, qualitative research revolves around subjective aspects such as people's opinions, verbal expressions, and occasional utilization of visuals. In qualitative research, our objective is to gain a comprehensive understanding of the qualities associated with a specific area or topic.
Which qualitative research method is the most commonly employed in UX design?
Primarily, we engage in one-on-one interviews (both moderated and unmoderated), group discussions, contextual inquiries, literature reviews, and participant observations. These methods allow us to explore and interpret behaviours. For instance, to gain insights into the shopping habits of pet owners, an effective strategy could involve observing their purchasing patterns in pet stores over extended periods and meticulously recording behaviours and interactions.
The next step involves analyzing these observations to identify patterns or commonalities, which can lead to developing theories about pet owners' buying behaviours. This process of documentation and analysis is the key to drawing meaningful conclusions and offering recommendations from qualitative data.
Most of our research practices in UX design can be categorized under qualitative research. The reason is simple. The complexity of human behaviour and the subjective nature of user experiences often make quantitative methods inadequate.
Through interviews and contextual inquiries, we can dive into understanding users' needs, preferences, and challenges, thereby informing design decisions that are empathetic and user-centric; hence why qual research strategies are usually better suited for UX design research.
I’ve been working on a (pretty) lengthy video for people interested in immigrating to Canada & working in tech. I’m planning to release the video sometime in March, so if this interests you, make sure to subscribe to my YouTube channel so you’ll be the first to know when it’s released.
I recorded a video on the topic because I saw how helpful my other video about getting a job in New Zealand was to many people.
If you’re looking for an easy introduction to quantitive data analysis, I’d highly recommend the following course teaching Python: Python A-Z for Data Science by Kirill Eremenko.
This is the course I’ve been studying. Let me know if you’d like to hear more about my experience once I finish the course.
This is it for this newsletter.
I’ll see you next time! Happy researching!